{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "google",
   "metadata": {},
   "source": [
    "##### Copyright 2025 Google LLC."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "apache",
   "metadata": {},
   "source": [
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    http://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "basename",
   "metadata": {},
   "source": [
    "# no_overlap_sample_sat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "link",
   "metadata": {},
   "source": [
    "<table align=\"left\">\n",
    "<td>\n",
    "<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/sat/no_overlap_sample_sat.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
    "</td>\n",
    "<td>\n",
    "<a href=\"https://github.com/google/or-tools/blob/main/ortools/sat/samples/no_overlap_sample_sat.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
    "</td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "doc",
   "metadata": {},
   "source": [
    "First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "install",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install ortools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "description",
   "metadata": {},
   "source": [
    "\n",
    "Code sample to demonstrate how to build a NoOverlap constraint.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "code",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ortools.sat.python import cp_model\n",
    "\n",
    "\n",
    "def no_overlap_sample_sat():\n",
    "    \"\"\"No overlap sample with fixed activities.\"\"\"\n",
    "    model = cp_model.CpModel()\n",
    "    horizon = 21  # 3 weeks.\n",
    "\n",
    "    # Task 0, duration 2.\n",
    "    start_0 = model.new_int_var(0, horizon, \"start_0\")\n",
    "    duration_0 = 2  # Python cp/sat code accepts integer variables or constants.\n",
    "    end_0 = model.new_int_var(0, horizon, \"end_0\")\n",
    "    task_0 = model.new_interval_var(start_0, duration_0, end_0, \"task_0\")\n",
    "    # Task 1, duration 4.\n",
    "    start_1 = model.new_int_var(0, horizon, \"start_1\")\n",
    "    duration_1 = 4  # Python cp/sat code accepts integer variables or constants.\n",
    "    end_1 = model.new_int_var(0, horizon, \"end_1\")\n",
    "    task_1 = model.new_interval_var(start_1, duration_1, end_1, \"task_1\")\n",
    "\n",
    "    # Task 2, duration 3.\n",
    "    start_2 = model.new_int_var(0, horizon, \"start_2\")\n",
    "    duration_2 = 3  # Python cp/sat code accepts integer variables or constants.\n",
    "    end_2 = model.new_int_var(0, horizon, \"end_2\")\n",
    "    task_2 = model.new_interval_var(start_2, duration_2, end_2, \"task_2\")\n",
    "\n",
    "    # Weekends.\n",
    "    weekend_0 = model.new_interval_var(5, 2, 7, \"weekend_0\")\n",
    "    weekend_1 = model.new_interval_var(12, 2, 14, \"weekend_1\")\n",
    "    weekend_2 = model.new_interval_var(19, 2, 21, \"weekend_2\")\n",
    "\n",
    "    # No Overlap constraint.\n",
    "    model.add_no_overlap([task_0, task_1, task_2, weekend_0, weekend_1, weekend_2])\n",
    "\n",
    "    # Makespan objective.\n",
    "    obj = model.new_int_var(0, horizon, \"makespan\")\n",
    "    model.add_max_equality(obj, [end_0, end_1, end_2])\n",
    "    model.minimize(obj)\n",
    "\n",
    "    # Solve model.\n",
    "    solver = cp_model.CpSolver()\n",
    "    status = solver.solve(model)\n",
    "\n",
    "    if status == cp_model.OPTIMAL:\n",
    "        # Print out makespan and the start times for all tasks.\n",
    "        print(f\"Optimal Schedule Length: {solver.objective_value}\")\n",
    "        print(f\"Task 0 starts at {solver.value(start_0)}\")\n",
    "        print(f\"Task 1 starts at {solver.value(start_1)}\")\n",
    "        print(f\"Task 2 starts at {solver.value(start_2)}\")\n",
    "    else:\n",
    "        print(f\"Solver exited with nonoptimal status: {status}\")\n",
    "\n",
    "\n",
    "no_overlap_sample_sat()\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
